Analytic Model for Web Anomalies Classification

In this paper, an analytic technique is proposed to improve the dynamic Web application quality and reliability. The technique integrates orthogonal defect classification (ODC), and Markov chain to classify as well as analyze the collective view of Web errors. The error collective view will be built from access logs and defect data. This classification technique will enable viewing the Web errors in page, path, and application contexts. This technique will help in developing reliable Web applications that benefit from the understanding of Web anomalies and past issues. The preliminary results of applying this approach to a case study from telecommunications industry are included to demonstrate its' viability.